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Results
In order to determine whether or not prior exposure to walking while blindfolded would result in adaptation to blind walking, a group of participants completed the blind walking task several times, either with prior exposure to walking around blindfolded (non-visual condition) or without prior exposure (visual condition). If prior exposure to blind walking results in adaptation, the participants should have walked farther when in the non-visual condition than when tested in the visual condition. Also, if adaptation has occurred, the participants in both conditions should have undershot less, and therefore walked farther, in Block 3 compared to Block 1.
Throughout the experiment, the subjects blindly walked to targets located various distances away from the participant. It was found that the distance from the subject to the target did not affect the subject’s accuracy to the target (Figure 1). The mean of the percent error from the target for the non-visual condition (M= -0.015, SD=0.1833) was smaller than the mean of the percent error from the target for the visual condition (M=-0.0338, SD=0.1719). The negative value means that, on average, the groups underestimated the distance. Blocks 1, 2, and 3, had a mean percent error of
0.0038 (SD=0.207), -0.0528 (SD=0.140), and -0.0242 (SD=0.176), respectively. It was found that the distance estimations in Block 3 were lower than the distance estimations made in Block 1 (Figure 2). A
2x3 (condition x block) repeated measures ANOVA was conducted, and it showed that there was no main effect of blocks (F(2,62) = 2.074, p> 0.05). There was also no main effect of conditions
(F(1,31)=0.198, p>0.05), and no interaction effect between blocks and conditions (F(2,62)=0.953, p>0.05) either (Table 1).

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Discussion
The purpose of this study was to determine whether or not prior exposure to blind walking leads to adaptation, and if this has an effect on one’s egocentric perception of distance. A group of subjects were tested across two conditions, a non-visual condition, in which they were allowed to practice walking blindly prior to completing a series of blind egocentric distance estimations, and a visual-condition, in which they were not exposed to blind-walking prior to the distance estimations. If adaptation had occurred, it would be expected that, when in the non-visual condition, the participants would have undershot less than when in the visual condition. Each participant completed
12 trials of distance estimations in both conditions; so, if the participants were adapting to walking blindly, they would have undershot the distances to the targets less as they completed more trials.
Therefore, the distance estimations in Block 3 should have been significantly higher, in either condition, compared to the distance estimations of Blocks 1 and 2. However, the results of this experiment do not coincide with the predictions.
The results depicted in Table 1 show that there were no significant effects between the two groups and among the blocks, and therefore, this indicates that the subjects did not adapt. Several scientists (Elliot 1986, 1987, Thomson 1983, 1987) use the blind walking test as a way to measure a subject’s perception of egocentric distance. However, if the subjects had adapted, they would have walked farther with more exposure to blind walking. So, after repeated trials of the blind walking test, and without taking adaptation into account, the results of these studies may be inaccurately depicting the subjects’ true perception of egocentric distance.

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Elliot (1987) used the blind walking test to measure his subjects’ perception of distance, and had allowed his subjects to practice walking blindly before completing the blind walking tasks. He noticed that the subjects tended to walk farther with more practice; however, he could not explain why he had witnessed this phenomenon (Elliot, 1987). So, to test the effects of prior exposure to blind walking on distance perception, this experiment specifically varied the type of practice (visual or non-visual) between groups to try to replicate the trend that Elliot (1987) observed. However, in this experiment, the results contradicted Elliot’s (1987) findings; the non-visual group did not overshoot more than the visual group even though they had more practice with blind-walking. Proffitt (2003) did not use the blind walking task; instead, he had his subjects walk on a tread mill either with optic flow (flow-condition) or without optic flow (no-flow condition), and then verbally report egocentric distance estimations to a target. Proffitt (2003) had found that his no-flow subjects had adapted to walking without optic flow and were therefore underestimating the distances to the targets less than the flow condition group. Although Proffitt was specifically controlling for blind-walking adaptation, verbally reporting distances is not a very accurate way to compare one subject’s distance perception to another since different people may have different understandings of distance measurements. So, in this experiment, the participants were allowed to walk to the target instead of verbally estimating the distance to the target. However, the results of this experiment do not coincide with Proffitt’s
(2003) results; the subjects did not adapt in this experiment since they were not underestimating the distances to the targets with increased exposure to blind walking.
The results obtained in this experiment were not as predicted, however this may be due to several sources of error. Firstly, there were only eight subjects participating in the study, so the results may not be very reliable. This is a very small sample size, and therefore, the variation between

ADAPTATION AND DISTANCE ESTIMATION
10 subjects may have skewed the results, even though a with-in subjects test was conducted in order to reduce the error due to variability. However, one of the eight subjects was only able to participate in one of the two conditions, so a ninth subject was used to complete the other condition for that participant. This would affect the validity of the with-in subjects test, since the variability of the ninth subject differs from the individual variability of the eighth subject. Also, such a small sample size is a poor representation of the entire population and therefore the results cannot be generalized to the population. The subjects were also aware of the true purpose of the experiment and may have been performing in a way that they thought the experimenter would want them to. This bias would have skewed the results since the participants were walking differently than they might have been walking had they not been aware of the purpose of the experiment. Also, due to inadequate funding, the blindfold that was used during the blind walking task was not of very high quality; there was a gap in the blindfold through which the subjects were able to look down and see the ground as they walked.
Therefore, the subjects had to be trusted not to cheat by looking down. If the subjects had been using their eyes to guide their feet by looking down through the gap in the blindfold, this would explain why the subjects did not adapt to blind-walking since they were not actually walking blindly. Also, the participants did not seem highly motivated when completing the blind walking tasks. When discussing the experiment with the subjects after it had finished, they explained that they were participating in the experiment merely because it was a requirement for a course they were enrolled in and did not care about putting much effort into the task. Since the subjects were not concentrating on the task, the results obtained are not accurate measurements of the subjects’ abilities since they were not exhibiting their true perceptions of distance. However, if this experiment were to be repeated, there are several ways to improve the study to account for the errors mentioned.

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There are many ways to improve this experiment in order to account for the various possible errors. First of all, the sample size should be increased in order to minimize the variability between subjects and render the results more reliable. Also, when using a with-in subjects study, each of the subjects should be tested on each of the conditions to maintain the validity of the results. The subjects should also be naïve to the purpose and hypotheses of the experiment so that they are not producing biased results. Furthermore, proper blindfolds or blackened goggles should be used instead of the ineffective blindfolds used in this experiment; the subjects should not be able to use their vision whatsoever when completing a blind-walking task. Also, in order to motivate the participants, some sort of compensation or award should be offered. Further research is needed to determine whether or not these factors may have significantly effected the results of this experiment.

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References
Elliot, D. (1986). Continuous visual information may be important after all: a failure to replicate
Thomson (1983). Journal of Experimental Psychology, 12(3), 388-391.
Elliot, D. (1987). The influence of walking speed and prior practice on locomotor distance estimation.
Journal of Motor Behavior, 19(4), 476-485.
Proffitt, D. R, Stefanucci, J, Banton, T, & Epstein, W. (2003). The role of effort in perceiving distance.
Psychological Science, 14(2), 107-112.
Thomson, J. A. (1986) Intermittent versus continuous visual control: a reply to Elliot. Journal of
Experimental Psychology: Human Perception and Performance, 12(3), 392-393.
Thomson, J. A. (1983). Is continuous visual monitoring necessary in visual guided locomotion?
Journal of Experimental Psychology: Human Perception and Performance, 9(3), 427-443.

Appendix
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Measure:MEASURE_1
Source condition Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Error(condition) block
Error(block) condition * block
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Error(condition*block) Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Tests of Within-Subjects Effects
Type III Sum of
Squares
.998
.998
.998
11.559
172.808
172.808
172.808
172.808
3.227
3.227
3.227
.998
156.580
156.580
156.580
156.580
11.559
11.559
11.559
3.227
104.985
104.985
104.985 df
1
1.000
Mean Square
.998
.998
1.000
1.000
62
56.334
59.648
31.000
2
1.935
2.000
1.000
31
31.000
31.000
31.000
2
1.817
1.924
1.000
62
59.973
62.000
.998
1.614
1.668
1.614
3.227
1.693
1.751
1.693
.998
5.051
5.051
5.051
5.051
5.780
6.361
6.008
11.559
2.787
3.068
2.897
5.574
.953
.953
.953
.953
2.074
2.074
2.074
2.074
F
.198
.198
.198
.198
Sig.
.660
.660
.660
.660
.134
.139
.136
.160
.391
.389
.391
.337

ADAPTATION AND DISTANCE ESTIMATION
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Tests of Within-Subjects Effects
Measure:MEASURE_1
Source condition Sphericity Assumed
Greenhouse-Geisser
Type III Sum of
Squares
.998
.998 df
1
1.000
Mean Square
.998
.998
F
.198
.198
Huynh-Feldt .998 1.000 .998 .198
Error(condition) block
Error(block)
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
11.559
172.808
172.808
172.808
172.808
3.227
3.227
3.227
.998
156.580
156.580
156.580
156.580
11.559
11.559
11.559
1.000
62
56.334
59.648
31.000
2
1.935
2.000
1.000
31
31.000
31.000
31.000
2
1.817
1.924
.998
5.051
5.051
5.051
5.051
5.780
6.361
6.008
11.559
2.787
3.068
2.897
5.574 condition * block 1.614
1.668
1.614
.953
.953
.953
Lower-bound
Error(condition*block) Sphericity Assumed
3.227
104.985
1.000
62
3.227
1.693
.953
Greenhouse-Geisser 104.985 59.973 1.751
1.693 Huynh-Feldt 104.985 62.000
Lower-bound 104.985 31.000 3.387
Table 1: Repeated measures ANOVA tests for within-subjects effects. No significant effects were found for any comparisons.
.198
2.074
2.074
2.074
2.074
Sig.
.660
.660
.660
.660
.134
.139
.136
.160
.391
.389
.391
.337

ADAPTATION AND DISTANCE ESTIMATION
15
0.15
0.1
0.05
0
NV
V
6 9 12 15
-0.05
-0.1
-0.15
Distance (m)
Figure 1: Percent error versus distance for the non-visual (NV) and visual (V) conditions with error bars of 1 standard deviation
0.06
0.04
0.02
0
-0.02
-0.04
-0.06
-0.08
-0.1
1 2 3
NV
V
Block
Figure 2: Percent error versus block for the non-visual (NV) and visual (V) conditions with error bars of 1 standard deviation